Special Issue Call for Papers:

Deep learning has triggered a revolution in speech processing. The revolution started from the successful application of deep neural networks to automatic speech recognition, and was quickly spread to other topics of speech processing, including speech analysis, speech denoising and separation, speaker and language recognition, speech synthesis, and spoken language understanding. This tremendous success is achieved by the advances of neural network technologies as well as the explosion of speech data and fast development of computing power.

Despite this success, deep learning based speech processing still has many challenges for real-world wide deployment. For example, when the distance between a speaker and a microphone array is larger than 10 meters, the word error rate of a speech recognizer may be as high as over 50%; end-to-end deep learning based speech processing systems have shown potential advantages over hybrid systems, however, they require large-scale labelled speech data; deep learning based speech synthesis has been highly competitive with human-sounding speech and much better than traditional methods, however, the models are not stable, lack controllability and are still too large and slow to be deployed into mobile and IoT devices.

Therefore, new methods and algorithms in deep learning and speech processing are needed to tackle the above challenges, as well as to yield novel insights into new directions and application.

This special issue aims to accelerate research progress by providing a forum for researchers and practitioners to present their latest contributions that advance theoretical and practical aspects of deep learning based speech processing techniques. The special issue will feature theoretical articles with novel new insights, creative solutions to key research challenges, and state-of-the-art speech processing algorithms/systems that demonstrate competitive performance with potential industrial impacts. The ideas addressing emerging problems and directions are also welcome.

Main Topics:

Topics of interest for this special issue include, but are not limited to:

Speaker separation

Speech denoising

Speech recognition

Speaker and language recognition

Speech synthesis

Audio and speech analysis

Multimodal speech processing

Submission Procedure:

Prospective authors should follow the standard author instructions for Neural Networks, and submit manuscripts online at http://ees.elsevier.com/neunet/. Authors should select “Speech Based on DL” when they reach the “Article Type” step and the “Request Editor” step in the submission process.